Abstract
We present the results of two research instruments fielded by SpillBill Insights between May and September 2026 to characterize how frequent travellers resolve the decisions that precede and accompany a trip: whether to travel alone or with others, how a companion is judged compatible, what conditions must hold before a traveller will extend trust to someone they have not met, and where existing tools succeed or fail at supporting these decisions.
We formalize each of these as a distinct decision problem, report the empirical distribution of outcomes observed across a thirty-respondent quantitative sample, and use a parallel set of qualitative interviews to characterize the reasoning underlying those outcomes. We further evaluate respondent reaction to a proposed AI-assisted travel-planning instrument and derive the conditions under which respondents indicate they would trust its output.
Our findings indicate that companion selection, not destination selection, is the primary point of friction in trip planning for this population, and that trust in an unfamiliar companion or an automated recommendation is granted only when specific, verifiable conditions are met.
Introduction
A trip, for the purposes of this paper, is treated not as a single decision but as a sequence of resolved sub-problems: who to travel with, if anyone; whether that companion, or set of companions, can be trusted; how the logistics of the trip are coordinated across everyone involved; and, increasingly, whether an automated system can be trusted to assist with any of the above. Existing consumer research on travel tends to treat these as demand-side preferences (destination, budget, season) rather than as decisions with their own failure conditions. This paper treats them as the latter.
We make the following contributions:
- We define a small set of terms (Companion Set, Compatibility Condition, Trust Event, Discovery Channel) sufficient to describe the companion-travel decision space precisely, and use them consistently throughout this paper.
- We report the empirical distribution of companion preference, compatibility criteria, and trust conditions observed in a thirty-respondent Quantitative Instrument, with exact counts alongside every reported percentage.
- We use a parallel Qualitative Instrument, consisting of unstructured interviews with frequent travellers in Bangalore and Hyderabad, to recover the reasoning behind the distributions observed above. Respondent statements are reproduced verbatim, with disfluencies removed but content and word choice preserved.
- We evaluate respondent reaction to a hypothetical AI-assisted travel-planning instrument and derive, from the data, the specific conditions under which respondents report they would act on its recommendations.
This paper does not attempt to establish population-level prevalence of any behaviour. Its scope is limited to characterizing, precisely, what a defined sample of frequent travellers reports, and to identifying which findings appear consistently across both instruments independently.
Definitions & Terminology
We begin by defining the terms used throughout this paper.
A respondent who has taken at least one overnight trip within the preceding six months, and who was screened into either instrument on this basis.
The set of people, other than the traveller, who accompany a given trip: empty (solo), a Known Set (friends, family, colleagues), or an Unknown Set (strangers, or an organised group with no prior relationship to the traveller).
An attribute of a prospective companion a respondent reports as necessary, though not necessarily sufficient, for that companion to be acceptable. Elicited as a bounded multi-select list; respondents selected up to three.
The point at which a traveller commits to travelling with a member of an Unknown Set, distinct from a Compatibility Condition, which describes what is evaluated rather than what causes the evaluation to resolve favourably.
Any tool, platform, or network through which a traveller locates trip information, a prospective companion, or both.
A structured survey (n = 30) combining single-select, multi-select, ranked, and rating-scale questions with a small number of open-ended prompts.
Fifteen-to-twenty-minute unstructured interviews with frequent travellers aged 18–30 in Bangalore and Hyderabad. Five interviews were completed and fully coded as of this writing; collection toward a larger sample is ongoing.
A reported percentage without further qualification refers to the Quantitative Instrument (n = 30). A reported statement in quotation marks is drawn from the Qualitative Instrument and reproduced in the respondent's own words.
Methodology
Thirty completed responses were collected. All thirty respondents had taken an overnight trip within the preceding six months, 73% (22/30) within the preceding month. Fifty-seven percent (17/30) were aged 25–34, the remainder 18–24. Ninety-three percent (28/30) reported an urban or Tier-1 residence, and 90% (27/30) reported actively searching online for new destinations or travel companions, a behaviour we treat as a proxy for engagement with the category.
Five interviews were completed and analysed as of this writing: four with respondents based in Bangalore, one in Hyderabad. Each followed a fixed discussion guide covering trip-planning narrative, companion decision-making, compatibility and trust, and reaction to a described (not demonstrated) travel-companion application concept. Interviews were transcribed and independently coded against a set of 142 descriptive codes generated from the corpus.
The Qualitative Instrument's sample (n = 5) is too small to support any claim of prevalence; its role here is restricted to explaining mechanism, not measuring frequency. Both instruments recruited specifically for frequent, digitally engaged travellers; neither supports inference about infrequent travellers, travellers over 45, or family travel with dependents.
The Companion Selection Problem
Given a free choice, a traveller selects a Companion Set from four available classes: Alone, Family, Friends/Co-workers, or Organised Group. We record the distribution of this selection across the Quantitative Instrument.
The empty Companion Set (Alone) is selected by a minority of respondents even under conditions of unconstrained choice. Of these three respondents, none reported an aversion to company as the reason; all three cited the absence of a suitable Companion Set or a preference for unstructured itineraries.
“Many times I thought of going with a few group people, but like-minded people are very few, so maybe that's the reason I haven't traveled with a group.”
Qualitative interview, Hyderabad
We asked respondents who selected a non-empty Companion Set to report their primary motivation:
Cost-sharing is not the primary motivation reported; it ranks second, behind social connection, by a margin of eleven percentage points, worth noting since product framing in this category has historically emphasized cost-sharing as the primary value proposition of companion travel.
Compatibility Conditions
We asked respondents to select, from a fixed list of six, up to three conditions that must hold for a prospective companion to be considered compatible.
Interests & Activities, the condition most commonly assumed in category discourse to define compatibility, ranks fourth of six, below both food/ accommodation preferences and budget alignment. Compatibility, as reported by this sample, is weighted toward operational alignment over taste alignment.
“If they complain a lot, that is the most annoying thing in a travel partner. If they find fault at everything and aren't flexible to plans, I would rule them out as a travel partner.”
“The qualities I prefer are good adaptation to the environment and a go-with-the-flow attitude, being easy to adapt to whatever situations happen.”
Neither statement references shared interests. Both describe temperament under logistical or financial constraint: convergent evidence, obtained independently across both instruments, that compatibility here is dominated by tolerance for friction rather than similarity of taste.
The Trust Problem
We asked whether respondents had travelled with, or would consider travelling with, a member of an Unknown Set.
A majority report willingness to extend a Trust Event to an unknown companion, but willingness here is high, not unconditional.
Read together, these indicate trust is not granted on the basis of platform assurance alone; it is granted on the basis of independently checkable evidence. This is corroborated in granular detail by the Qualitative Instrument, in which every respondent, unprompted, described a manual verification process already performed in the absence of any tool designed to support it.
“Number one, I would look them up on social media, Meta or LinkedIn, to see if they're safe to travel with. Second, I'd see if there's some shared interest.”
“I would give this a 50-50 chance of being solved, since people impersonate themselves as good people, and only when you meet them in person do you find out their true face.”
Qualitative interview, Bangalore
This statement distinguishes two problems often conflated in product design: verifying a person exists and has a history (T1/T2), and verifying their represented identity matches their actual disposition, addressed per this respondent, only by direct contact (T3). A system satisfying T1 and T2 without a mechanism resembling T3 should not be assumed to have resolved the Trust Problem for this population.
Discovery Channel Analysis
Respondents reported using multiple channels concurrently rather than a single primary channel.
No single channel is used to the exclusion of others. We interpret this not as an absence of demand for a consolidated channel, but as an absence of one respondents currently trust to be sufficient on its own.
“I wish there was one platform for personalized, trustworthy travel recommendations instead of searching across multiple apps and forums.”
A second, independently recurring theme concerns the integrity of the information available through existing channels: a stated suspicion that reviews and ratings are synthetically generated.
“Hotel booking, which many prefer, ratings doesn't look genuine at times, it looks AI-generated.”
The Coordination Problem
Where Sections 6 and 7 concern selecting and trusting a companion, this section concerns what happens after a Companion Set has been agreed upon. Every interview independently surfaced the same primary point of failure: schedule alignment across the group.
“Dates. Everybody's schedule is busy, and I think the most difficult thing is the dates.”
“The first stage where it falls apart is the scheduling of everyone: if not everyone is free, it easily falls apart.”
Enjoyment of the planning process itself was reported as low to moderate, even among respondents who described themselves as capable planners.
“Out of a scale of 1 to 10, I would enjoy this process 4 out of 10, because it takes a lot of work: the effort of talking to people, the effort of researching options.”
We distinguish the Coordination Problem from the Trust Problem deliberately. Trust is a slow, evidence-dependent condition a product can only partially accelerate. Coordination (aligning calendars, agreeing a shared budget, resolving a decision among several people) is a logistics problem, and is, in principle, more directly addressable by software than trust is, yet it received comparatively little emphasis relative to trust and discovery. We read this as under-addressed relative to its tractability, not unimportant.
Evaluation of an AI-Assisted Travel Layer
Respondents were shown a written description of a hypothetical app (travel discovery, companion matching, and an embedded AI assistant) with no product demonstrated, and rated its perceived usefulness on a five-point scale.
Ninety percent rated the concept 4 or 5. We report this cautiously: concept-description scores of this kind run higher than post-adoption satisfaction, as evidence the concept does not conflict with any need identified elsewhere in this paper.
No feature exceeds 40%, and the full set spans thirteen points. We interpret this as respondents conceiving of the need as one connected process (locate a companion, plan, book, remain coordinated) rather than a menu of independent features.
The leading condition is independent verifiability, not accuracy or personalization, consistent with the distrust of AI-generated reviews noted in Section 7. Fifty percent require a human fallback; we treat this as evidence against a fully automated, no-escalation design for this category.
Sample Characterization & External Validity
The Quantitative Instrument's sample is not representative of the general population of travellers; it was constructed to recruit specifically engaged, frequent travellers, and the sample's characteristics reflect that recruitment.
We regard this profile as appropriate to the research question (understanding the traveller most likely to adopt a travel-planning or companion product) but explicitly out of scope for any claim about travellers outside this profile, including travellers over 45 and family travel involving dependents.
Discussion
Taken together, the findings above support four conclusions:
- Companion selection is resolved by a large majority (90%, 27/30) in favour of a non-empty Companion Set, and cost-sharing is a secondary, not primary, motivation for that choice.
- Compatibility is weighted toward operational tolerance (shared budget, meals, accommodation) over shared taste in activities.
- The Trust Problem is not a binary willingness question; willingness is high (73%) but conditional on independently checkable evidence, and existing Discovery Channels carry their own stated trust deficit.
- The Coordination Problem (principally schedule alignment) is the most consistently cited cause of trip failure, and is comparatively more tractable than the Trust Problem, yet appears less prioritized in respondent discourse.
None of these four findings are specific to companion-matching products. Any travel product involving more than one traveller in a single decision, such as a group booking flow, a shared-itinerary tool, or a split-payment feature, will encounter the Compatibility, Trust, and Coordination Problems the moment a Companion Set larger than one person is involved, which, per Section 4, describes 90% of the trips reported to us.
Conclusion
We have presented empirical evidence, drawn from two independent instruments, that trip planning for frequent travellers is structured around companion selection, trust, and coordination rather than destination or price alone. We have shown that trust in an unfamiliar companion, and trust in an automated recommendation, are granted under similar conditions: independently checkable evidence, rather than an unelaborated assurance of safety or quality. We regard the Coordination Problem, given its tractability relative to trust, as the most immediately addressable of the four findings summarized above, and the Trust Problem as the one most likely to determine whether a companion-travel product is adopted at all.
About SpillBill Insights
SpillBill Insights conducts primary consumer research to characterize the behaviours, motivations, and unmet needs underlying consumer decisions, combining structured quantitative instruments with unstructured qualitative interviews. This report reflects fieldwork as of September 2026. The Quantitative Instrument (n = 30) is complete; the Qualitative Instrument (n = 5 completed, additional collection ongoing) should be read as illustrative of mechanism rather than as a population estimate.